Výsledky vyhledávání - Sparse stacked denoising autoencoder (SSDAE)

A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings

Autoři: Ping Liu Peng Fan Hui Wang a další

Zdroj: Measurement. 146:305-314

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://ui.adsabs.harvard.edu/abs/2019Meas..146..305S/abstract
https://www.sciencedirect.com/science/article/pii/S0263224119305950

Flatness pattern recognition based on stacked sparse denoising autoencoder and improved Osprey optimisation algorithm kernel-extreme learning machine

Autoři: Zhou, Yaluo Zhang, Shaochuan Liu, Wenguang a další

Přispěvatelé: Zhou, Yaluo Zhang, Shaochuan Liu, Wenguang a další

Zdroj: Ironmaking & Steelmaking: Processes, Products and Applications ; ISSN 0301-9233 1743-2812

Dostupnost: https://doi.org/10.1177/03019233251324775
https://journals.sagepub.com/doi/pdf/10.1177/03019233251324775
https://journals.sagepub.com/doi/full-xml/10.1177/03019233251324775

Fault Diagnosis of Rolling Bearing Based on Multiscale Intrinsic Mode Function Permutation Entropy and a Stacked Sparse Denoising Autoencoder

Autoři: Juying Dai Jian Tang Faming Shao a další

Zdroj: Applied Sciences, Vol 9, Iss 13, p 2743 (2019)

Témata: IMFs, multiscale permutation entropy, stacked sparse denoising autoencoder, fault diagnosis, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/9/13/2743; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/513f8bf811eb491dab82fad9ce1ea4c2

Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine.

Autoři: Zhang, Nana Ying, Shi Zhu, Kun a další

Zdroj: IET Software (Wiley-Blackwell). Feb2022, Vol. 16 Issue 1, p29-47. 19p.

Témata: *COMPUTER software quality control, *COMPUTER software industry, *ELECTRONIC data processing, FEATURE extraction, PARTICLE swarm optimization

Toward Robust Fault Identification of Complex Industrial Processes Using Stacked Sparse-Denoising Autoencoder With Softmax Classifier.

Autoři: Liu J Xu L Xie Y a další

Zdroj: IEEE transactions on cybernetics [IEEE Trans Cybern] 2023 Jan; Vol. 53 (1), pp. 428-442. Date of Electronic Publication: 2022 Dec 23.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101609393 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2168-2275 (Electronic) Linking ISSN: 21682267 NLM ISO Abbreviation: IEEE Trans Cybern Subsets: PubMed not MEDLINE; MEDLINE

Learning social representations with deep autoencoder for recommender system.

Autoři: Pan, Yiteng He, Fazhi Yu, Haiping

Zdroj: World Wide Web; Jul2020, Vol. 23 Issue 4, p2259-2279, 21p

Témata: SOCIAL learning, COLLECTIVE representation, RECOMMENDER systems, MATRIX decomposition, SOCIAL influence, SOCIAL interaction, SOCIAL problems

A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques.

Autoři: Kumar, Santosh Kumar, Sunil Shafi, Mehak a další

Zdroj: Multimedia Tools & Applications; Sep2022, Vol. 81 Issue 21, p31075-31106, 32p

Témata: ENDANGERED species, FEATURE extraction, FACE, EXTRACTION techniques

Fault Diagnosis of Rolling Bearing Based on Multiscale Intrinsic Mode Function Permutation Entropy and a Stacked Sparse Denoising Autoencoder.

Autoři: Dai, Juying Tang, Jian Shao, Faming a další

Zdroj: Applied Sciences (2076-3417); Jul2019, Vol. 9 Issue 13, p2743, 28p

Témata: HILBERT-Huang transform, FAULT diagnosis, ENTROPY (Information theory), PERMUTATIONS, DEEP learning

Korporace: INTERNATIONAL Monetary Fund, SOCIETY of Automotive Engineers

Digital Image Forgery Detection Using Cyclic Symmetry Convolutional Neural Network.

Autoři: S., Shashikala G. K., Ravikumar

Zdroj: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 1, p368-379, 12p

Témata: CONVOLUTIONAL neural networks, FEATURE selection, DIGITAL images, FEATURE extraction, AUTOENCODERS

Incipient fault detection and process monitoring of thermal power plant pulverizing system based on deep representation learning.

Autoři: Zeng, Lei Zhang, Xin Yu, Ke a další

Zdroj: Transactions of the Institute of Measurement & Control; Nov2025, Vol. 47 Issue 15, p3111-3123, 13p

Témata: FAULT diagnosis, DEEP learning, STEAM power plants, K-nearest neighbor classification, PROCESS control systems, FEATURE extraction

Automatic fault diagnosis of rolling bearings under multiple working conditions based on unsupervised stack denoising autoencoder.

Autoři: Wang, Lei Rao, Hang Dong, Zhengcheng a další

Zdroj: Structural Health Monitoring; Sep2024, Vol. 23 Issue 5, p3084-3104, 21p

Témata: AUTOENCODERS, DEEP learning, ROLLER bearings, DIAGNOSIS, ALGORITHMS, FEATURE extraction

A novel optimization-driven deep learning framework for the detection of DDoS attacks.

Autoři: Batchu, Raj Kumar Bikku, Thulasi Thota, Srinivasarao a další

Zdroj: Scientific Reports; 11/14/2024, Vol. 12 Issue 1, p1-16, 16p

A deep neural network with hybrid spotted hyena optimizer and grasshopper optimization algorithm for copy move forgery detection.

Autoři: Gupta, Ruchi Singh, Pushpa Alam, Tanweer a další

Zdroj: Multimedia Tools & Applications; Jul2023, Vol. 82 Issue 16, p24547-24572, 26p

Témata: OPTIMIZATION algorithms, FORGERY, GRASSHOPPERS, EVIDENCE gaps

Applications of Markov Decision Process Model and Deep Learning in Quantitative Portfolio Management during the COVID-19 Pandemic.

Autoři: Yue, Han Liu, Jiapeng Zhang, Qin

Zdroj: Systems; Oct2022, Vol. 10 Issue 5, pN.PAG-N.PAG, 20p

Témata: DEEP learning, REINFORCEMENT learning, MARKOV processes, DECISION making, COVID-19 pandemic, REWARD (Psychology)

A Novel Anti-Risk Method for Portfolio Trading Using Deep Reinforcement Learning.

Autoři: Yue, Han Liu, Jiapeng Tian, Dongmei a další

Zdroj: Electronics (2079-9292); May2022, Vol. 11 Issue 9, pN.PAG-N.PAG, 13p

Témata: REINFORCEMENT learning, DOW Jones industrial average, DEEP learning, RESISTANCE training, FEATURE extraction

A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion.

Autoři: Ghosh, Swarup Kr Biswas, Biswajit Ghosh, Anupam

Zdroj: Evolutionary Intelligence; Mar2021, Vol. 14 Issue 1, p133-149, 17p

Semi-supervised denoising autoencoder with multiple consistency regularization for process fault classification.

Autoři: Guo, Xiaoping Guo, Qingyu Li, Yuan

Zdroj: Engineering Research Express; Sep2025, Vol. 7 Issue 3, p1-19, 19p

SPR: Malicious traffic detection model for CTCS-3 in railways.

Autoři: Siyang Zhou Wenjiang Ji Xinhong Hei a další

Zdroj: High-speed Railway; Jun2025, Vol. 3 Issue 2, p105-115, 11p

Témata: EXTREME learning machines, TRAFFIC monitoring, AUTOENCODERS, INDUSTRIAL controls manufacturing, MACHINE learning

Operating performance assessment based on stacked performance‐relevant enhanced denoising auto‐encoder for industrial processes.

Autoři: Liu, Yan Ma, Zhe Wang, Fuli a další

Zdroj: Canadian Journal of Chemical Engineering; Apr2024, Vol. 102 Issue 4, p1509-1521, 13p

Témata: MANUFACTURING processes, AUTHENTIC assessment, FEATURE extraction, LEACHING, CYANIDES

Copy-Move Forgery Detection and Classification Using Improved Butterfly Optimization Algorithm-based Convolutional Neural Network.

Autoři: S., Shashikala G. K., Ravikumar

Zdroj: International Journal of Intelligent Engineering & Systems; 2024, Vol. 17 Issue 1, p869-879, 11p

Témata: CONVOLUTIONAL neural networks, FORGERY, OPTIMIZATION algorithms, FEATURE extraction, FEATURE selection